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{
  "model1_classification": {
    "task": "Cargo Classification",
    "num_classes": 43,
    "class_names": [
      "appliances",
      "auto_parts",
      "bags",
      "banana",
      "batteries",
      "beverages",
      "cables",
      "canned_food",
      "ceramic",
      "chemicals",
      "cleaning",
      "clothes",
      "cooking_oil",
      "cosmetics",
      "electronics",
      "fruits",
      "furniture",
      "glass",
      "kitchenware",
      "lubricants",
      "machinery",
      "meat",
      "medical",
      "milk",
      "motorcycle",
      "nuts",
      "other",
      "paper",
      "pipes",
      "plastic",
      "rice",
      "seeds",
      "shoes",
      "snacks",
      "spices",
      "steel",
      "sugar",
      "tea",
      "tires",
      "tools",
      "toys",
      "weapons",
      "wood"
    ]
  },
  "model2_anomaly": {
    "task": "Concealment Detection",
    "num_classes": 2,
    "class_names": [
      "match",
      "no_match"
    ],
    "note": "Already trained - see concealment folder"
  },
  "model3_risk": {
    "task": "Risk Assessment",
    "num_classes": 5,
    "class_names": [
      "risk_0_safe",
      "risk_1_2_low",
      "risk_3_medium",
      "risk_4_high",
      "risk_5_critical"
    ]
  },
  "normalize": {
    "mean": [
      0.485,
      0.456,
      0.406
    ],
    "std": [
      0.229,
      0.224,
      0.225
    ]
  }
}